Paradoxical Phenotype of Fibromyalgia Neutrophils with Elevated Baseline Inflammation but Blunted Response to Stimulation
Bibliographic record
Abstract
Abstract Fibromyalgia (FM) is a severe pain condition of unknown etiology. Here, we performed transcriptomics analyses of peripheral neutrophils exposed to an inflammatory stimulus, comparing responses of neutrophils obtained from FM patients versus healthy controls. We observed a state of inflammation in neutrophils from FM patients. However, FM neutrophils were unable to efficiently respond to lipopolysaccharide (LPS). This impairment was especially characteristic of FM patients with no improvement after 5 years after diagnosis in comparison with those who did improve. Blood plasma from FM patients directly stimulated a wide range of primary sensory neurons in vitro and induced pain hypersensitivity when injected into mice. Further analysis identified NF-κB suppression as a key biological process associated with low-grade inflammation and LPS non-responsiveness in neutrophils from FM patients. The clinically used NF-κB activator, bryostatin, alleviated hypersensitivity in mice treated with FM plasma, pointing to controlled inflammation induction through reactivation of the NF-κB pathway as a possible therapeutic target for FM treatment. Our whole blood single-cell RNA sequencing replicated this NF-κB-driven inflammation observed in bulk analyses transcriptomics in FM patients and revealed that this inflammatory signature is strongly pronounced not only in neutrophils, but across a broad range of immune cells.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".